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We investigate the suitability of selected measures of complexity based onrecurrence quantification analysis and recurrence networks for anidentification of pre-seizure states in multi-day, multi-channel, invasiveelectroencephalographic recordings from five epilepsy patients. We employseveral statistical techniques to avoid spurious findings due to variousinfluencing factors and due to multiple comparisons and observe precursorystructures in three patients. Our findings indicate a high congruence amongmeasures in identifying seizure precursors and emphasize the current notion ofseizure generation in large-scale epileptic networks. A final judgment of thesuitability for field studies, however, requires evaluation on a largerdatabase.

Evaluation of selected recurrence measures in discriminating pre-ictal and inter-ictal periods from epileptic EEG data